Abstract: This minisymposium focuses on imaging methodologies, mathematical models, and computational algorithms on inverse problems for biomedical applications. The imaging problems in this topic can be formulated as inverse problems that are intrinsically nonlinear. Experiences over the last three decades showed that symbiotic interplay among theoretical mathematics, computational mathematics, and experiments is crucial for understanding and solving these nonlinear problems in practice. With this minisymposium we hope to introduce inverse problems related to biomedical applications, to show how a various methods can solve them, and to present new schemes to solve these inverse problems.

MS-Tu-D-08-113:30--14:00Monitoring of regional lung monotonic conductivity changes using EITZHOU, LIANGDONG (Yonsei Univ.)Abstract: This paper presents a monotonicity-based spatiotemporal conductivity imaging method for continuous regional lung monitoring using electrical impedance tomography(EIT). EIT boundary data can be decomposed into pulmonary, cardiac and other parts using their different periodic nature. Then, the time-differential current-voltage operator corresponding to lung ventilation can be viewed as either semi-positive or semi-negative definite because of monotonic conductivity changes within lung region. The monotonicity constraints enable us to improve the image quality of lung EIT.

MS-Tu-D-08-214:00--14:30Functional magnetic resonance electrical impedance tomography based on skipped k-space dataSong, Yizhuang (Shandong Normal Univ.)Abstract: Neural activity associated with opening of ion channels in cell membranes causes an increase in conductivity, which may be probed by developing a fast MREIT technique. We present a method of functional MREIT (fMREIT), which aims to visualize local conductivity changes related to neuronal activity using the technique called Magnetic Resonance Electrical Impedance Tomography (MREIT). The key idea we used is skipping the time consuming phase encoding lines. Numerical experiments validate our proposed method.

MS-Tu-D-08-314:30--15:00Tissue characterization at variable depth using localized planar EITKwon, Hyeuknam (Yonsei)Abstract: This paper presents a multi-scale method of measuring admittivity spectra using the bioimpedance spectroscopy (BIS) having a probe of 64x64 miniaturized electrodes. The proposed method evaluates the average admittivity values of voxels with varying their sizes with suitable combination of BIS data. This method allow to evaluates depth dependent admittivity distribution.

MS-Tu-D-08-415:00--15:30Reconstruction of EIT images via patch based sparse representation over learned dictionariesQi, Wang (Tianjin Polytechnic Univ.)Abstract: This paper presents the study of a new sparse reconstruction method for electrical impedance tomography (EIT). The EIT images are reconstructed based on adaptive patch-based sparse representation. Furthermore, the sparse dictionary is optimized during iteration. Simulation results are provided and compared with that of traditional reconstruction methods.